Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:
The method for the research-field-mapping can be reviewed here:
The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:
The present analysis is based on the following seed articles:
| AU | PY | TI | JI |
|---|---|---|---|
| THOMAS A | 2021 | ‘HEART OF STEEL’: HOW TRADE UNIONS LOBBY THE EUROPEAN UNION OVER EMISSIONS TRADING | ENVIRON. POLIT. |
| MARTIN L | 2020 | HOW TO RETAIN MOTIVATED EMPLOYEES IN THEIR JOBS? | ECON. IND. DEMOCR. |
| ALBANESE A;COCKX B;THUY Y | 2020 | WORKING TIME REDUCTIONS AT THE END OF THE CAREER: DO THEY PROLONG THE TIME SPENT IN EMPLOYMENT? | EMPIR. ECON. |
| CATANZARO D;PESENTI R;WOLSEY L | 2020 | ON THE BALANCED MINIMUM EVOLUTION POLYTOPE | DISCRETE OPTIM. |
| BURZYNSKI M;DEUSTER C;DOCQU… | 2020 | GEOGRAPHY OF SKILLS AND GLOBAL INEQUALITY | J. DEV. ECON. |
| WALTHER OJ;TENIKUE M;TRÉMOL… | 2019 | ECONOMIC PERFORMANCE, GENDER AND SOCIAL NETWORKS IN WEST AFRICAN FOOD SYSTEMS | WORLD DEV. |
| POUSSING N | 2019 | DOES CORPORATE SOCIAL RESPONSIBILITY ENCOURAGE SUSTAINABLE INNOVATION ADOPTION? EMPIRICAL EVIDENC… | CORP. SOC. RESPONSIB. ENVIR… |
| COSAERT S | 2019 | WHAT TYPES ARE THERE? | COMPUT. ECON. |
| MOTHE C;NGUYEN-THI UT | 2017 | PERSISTENT OPENNESS AND ENVIRONMENTAL INNOVATION: AN EMPIRICAL ANALYSIS OF FRENCH MANUFACTURING F… | J. CLEAN. PROD. |
| NAGORE GARCÍA A;VAN SOEST A | 2017 | NEW JOB MATCHES AND THEIR STABILITY BEFORE AND DURING THE CRISIS | INT. J. MANPOW. |
Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.
Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_liser_lm.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.
Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA, Blei et al., 2003) is an example of topic model and is used to classify text in a document to a particular topic.
LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.
LDAvis is a web-based interactive visualisation of topics estimated using LDA (Sievert & Shirley, 2014). It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.
The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.
The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.
The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.
Note: This analysis refers the co-citation analysis,
where the cited references and not the original publications are the
unit of analysis. See tab Technical descriptionfor
additional explanations
In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.
| name | dgr_int | dgr |
|---|---|---|
| Knowledge Base 1: KB 1: Knowledge and innovation in firms (n = 3260, density =3.42) | ||
| COHEN W.M. LEVINTHAL D.A. ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION (1990) | 16181 | 19103 |
| LAURSEN K. SALTER A. OPEN FOR INNOVATION: THE ROLE OF OPENNESS IN EXPLAINING INNOVATION PERFORMANCE AMONG UK MANUFACTURING FIRMS (2006) | 9613 | 10417 |
| ZAHRA S.A. GEORGE G. ABSORPTIVE CAPACITY: A REVIEW RECONCEPTUALIZATION AND EXTENSION (2002) | 7580 | 8657 |
| KATILA R. AHUJA G. SOMETHING OLD SOMETHING NEW: A LONGITUDINAL STUDY OF SEARCH BEHAVIOR AND NEW PRODUCT INTRODUCTION (2002) | 6587 | 7080 |
| DAHLANDER L. GANN D.M. HOW OPEN IS INNOVATION? (2010) | 5968 | 6436 |
| LAURSEN K. SALTER A. OPEN FOR INNOVATION: THE ROLE OF OPENNESS IN EXPLAINING INNOVATION PERFORMANCE AMONG U.K. MANUFACTURING FIRMS (2006) | 4806 | 5260 |
| CASSIMAN B. VEUGELERS R. IN SEARCH OF COMPLEMENTARITY IN INNOVATION STRATEGY: INTERNAL R&D AND EXTERNAL KNOWLEDGE ACQUISITION (2006) | 4763 | 5270 |
| LEIPONEN A. HELFAT C.E. INNOVATION OBJECTIVES KNOWLEDGE SOURCES AND THE BENEFITS OF BREADTH (2010) | 4602 | 4929 |
| MARCH J.G. EXPLORATION AND EXPLOITATION IN ORGANIZATIONAL LEARNING (1991) | 4438 | 5013 |
| GRANT R.M. TOWARD A KNOWLEDGE-BASED THEORY OF THE FIRM (1996) | 4368 | 5039 |
| Knowledge Base 2: KB 2: Human ressource management and firm productivity (n = 2856, density =3.22) | ||
| HUSELID M.A. THE IMPACT OF HUMAN RESOURCE MANAGEMENT PRACTICES ON TURNOVER PRODUCTIVITY AND CORPORATE FINANCIAL PERFORMANCE (1995) | 7484 | 7863 |
| BLAU P.M. (1964) | 5504 | 5896 |
| JIANG K. LEPAK D.P. HU J. BAER J.C. HOW DOES HUMAN RESOURCE MANAGEMENT INFLUENCE ORGANIZATIONAL OUTCOMES? A META-ANALYTIC INVESTIGATION OF MEDIATIN… | 3370 | 3525 |
| GAGNÉ M. DECI E.L. SELF-DETERMINATION THEORY AND WORK MOTIVATION (2005) | 3331 | 3362 |
| COMBS J. LIU Y. HALL A. KETCHEN D. HOW MUCH DO HIGH-PERFORMANCE WORK PRACTICES MATTER? A META-ANALYSIS OF THEIR EFFECTS ON ORGANIZATIONAL PERFORMAN… | 3317 | 3421 |
| MACDUFFIE J.P. HUMAN RESOURCE BUNDLES AND MANUFACTURING PERFORMANCE: ORGANIZATIONAL LOGIC AND FLEXIBLE PRODUCTION SYSTEMS IN THE WORLD AUTO INDUSTR… | 2822 | 2934 |
| ARTHUR J.B. EFFECTS OF HUMAN RESOURCE SYSTEMS ON MANUFACTURING PERFORMANCE AND TURNOVER (1994) | 2689 | 2774 |
| TAKEUCHI R. LEPAK D.P. WANG H. TAKEUCHI K. AN EMPIRICAL EXAMINATION OF THE MECHANISMS MEDIATING BETWEEN HIGH-PERFORMANCE WORK SYSTEMS AND THE PERFO… | 2592 | 2637 |
| LIAO H. TOYA K. LEPAK D.P. HONG Y. DO THEY SEE EYE TO EYE? MANAGEMENT AND EMPLOYEE PERSPECTIVES OF HIGH-PERFORMANCE WORK SYSTEMS AND INFLUENCE PROC… | 2590 | 2635 |
| BOSELIE P. DIETZ G. BOON C. COMMONALITIES AND CONTRADICTIONS IN HRM AND PERFORMANCE RESEARCH (2005) | 2556 | 2618 |
| Knowledge Base 3: KB 3: Economic growth (n = 1859, density =2.18) | ||
| SOLOW R.M. A CONTRIBUTION TO THE THEORY OF ECONOMIC GROWTH (1956) | 1491 | 1536 |
| LUCAS R.E. ON THE MECHANICS OF ECONOMIC DEVELOPMENT (1988) | 1427 | 1457 |
| ROMER P.M. ENDOGENOUS TECHNOLOGICAL CHANGE (1990) | 1107 | 1248 |
| MANKIW N.G. ROMER D. WEIL D.N. A CONTRIBUTION TO THE EMPIRICS OF ECONOMIC GROWTH (1992) | 933 | 954 |
| AUTOR D.H. LEVY F. MURNANE R.J. THE SKILL CONTENT OF RECENT TECHNOLOGICAL CHANGE: AN EMPIRICAL EXPLORATION (2003) | 844 | 850 |
| HALL R.E. JONES C.I. WHY DO SOME COUNTRIES PRODUCE SO MUCH MORE OUTPUT PER WORKER THAN OTHERS? (1999) | 837 | 837 |
| ROMER P.M. INCREASING RETURNS AND LONG-RUN GROWTH (1986) | 767 | 861 |
| BARRO R.J. ECONOMIC GROWTH IN A CROSS SECTION OF COUNTRIES (1991) | 760 | 769 |
| GROGGER J. HANSON G.H. INCOME MAXIMIZATION AND THE SELECTION AND SORTING OF INTERNATIONAL MIGRANTS (2011) | 747 | 750 |
| BLUNDELL R. BOND S. INITIAL CONDITIONS AND MOMENT RESTRICTIONS IN DYNAMIC PANEL DATA MODELS (1998) | 746 | 877 |
| Knowledge Base 4: KB 4: Corporate social responsibility and firm performance (n = 1749, density =5.4) | ||
| MCWILLIAMS A. SIEGEL D. CORPORATE SOCIAL RESPONSIBILITY: A THEORY OF THE FIRM PERSPECTIVE (2001) | 7475 | 8090 |
| ORLITZKY M. SCHMIDT F.L. RYNES S.L. CORPORATE SOCIAL AND FINANCIAL PERFORMANCE: A META-ANALYSIS (2003) | 4592 | 5114 |
| SURROCA J. TRIBÓ J.A. WADDOCK S. CORPORATE RESPONSIBILITY AND FINANCIAL PERFORMANCE: THE ROLE OF INTANGIBLE RESOURCES (2010) | 3090 | 3389 |
| FREEMAN R.E. (1984) | 3046 | 3364 |
| MCWILLIAMS A. SIEGEL D.S. WRIGHT P.M. CORPORATE SOCIAL RESPONSIBILITY: STRATEGIC IMPLICATIONS (2006) | 2875 | 3039 |
| MARGOLIS J.D. WALSH J.P. MISERY LOVES COMPANIES: RETHINKING SOCIAL INITIATIVES BY BUSINESS (2003) | 2635 | 2746 |
| CARROLL A.B. A THREE-DIMENSIONAL CONCEPTUAL MODEL OF CORPORATE PERFORMANCE (1979) | 2194 | 2364 |
| MCWILLIAMS A. SIEGEL D. CORPORATE SOCIAL RESPONSIBILITY AND FINANCIAL PERFORMANCE: CORRELATION OR MISSPECIFICATION? (2000) | 2116 | 2256 |
| CAMPBELL J.L. WHY WOULD CORPORATIONS BEHAVE IN SOCIALLY RESPONSIBLE WAYS? AN INSTITUTIONAL THEORY OF CORPORATE SOCIAL RESPONSIBILITY (2007) | 2067 | 2288 |
| WADDOCK S.A. GRAVES S.B. THE CORPORATE SOCIAL PERFORMANCE-FINANCIAL PERFORMANCE LINK (1997) | 1964 | 2049 |
| Knowledge Base 5: KB 5: Environmental innovation in firms (n = 1568, density =6.53) | ||
| DE MARCHI V. ENVIRONMENTAL INNOVATION AND R&D COOPERATION: EMPIRICAL EVIDENCE FROM SPANISH MANUFACTURING FIRMS (2012) | 5510 | 7307 |
| KESIDOU E. DEMIREL P. ON THE DRIVERS OF ECO-INNOVATIONS: EMPIRICAL EVIDENCE FROM THE UK (2012) | 3439 | 3932 |
| TRIGUERO A. MORENO-MONDÉJAR L. DAVIA M.A. DRIVERS OF DIFFERENT TYPES OF ECO-INNOVATION IN EUROPEAN SMES (2013) | 3018 | 3512 |
| HORBACH J. DETERMINANTS OF ENVIRONMENTAL INNOVATION—NEW EVIDENCE FROM GERMAN PANEL DATA SOURCES (2008) | 2463 | 2929 |
| PORTER M.E. VAN DER LINDE C. TOWARD A NEW CONCEPTION OF THE ENVIRONMENT-COMPETITIVENESS RELATIONSHIP (1995) | 2413 | 3061 |
| CARRILLO-HERMOSILLA J. DEL RÍO P. KÖNNÖLÄ T. DIVERSITY OF ECO-INNOVATIONS: REFLECTIONS FROM SELECTED CASE STUDIES (2010) | 2262 | 2645 |
| DEMIREL P. KESIDOU E. STIMULATING DIFFERENT TYPES OF ECO-INNOVATION IN THE UK: GOVERNMENT POLICIES AND FIRM MOTIVATIONS (2011) | 2015 | 2253 |
| CAINELLI G. DE MARCHI V. GRANDINETTI R. DOES THE DEVELOPMENT OF ENVIRONMENTAL INNOVATION REQUIRE DIFFERENT RESOURCES? EVIDENCE FROM SPANISH MANUFAC… | 1901 | 2344 |
| WAGNER M. ON THE RELATIONSHIP BETWEEN ENVIRONMENTAL MANAGEMENT ENVIRONMENTAL INNOVATION AND PATENTING: EVIDENCE FROM GERMAN MANUFACTURING FIRMS (2007) | 1848 | 2096 |
| GHISETTI C. MARZUCCHI A. MONTRESOR S. THE OPEN ECO-INNOVATION MODE. AN EMPIRICAL INVESTIGATION OF ELEVEN EUROPEAN COUNTRIES (2015) | 1808 | 2422 |
| Knowledge Base 6: KB 6: Social network and social capital (n = 1087, density =5.4) | ||
| BURT R.S. (1992) | 3382 | 3959 |
| MCPHERSON M. SMITH-LOVIN L. COOK J.M. BIRDS OF A FEATHER: HOMOPHILY IN SOCIAL NETWORKS (2001) | 2385 | 2482 |
| COLEMAN J.S. SOCIAL CAPITAL IN THE CREATION OF HUMAN CAPITAL (1988) | 2297 | 2625 |
| BURT R.S. (2005) | 1813 | 1973 |
| GRANOVETTER M.S. THE STRENGTH OF WEAK TIES (1973) | 1762 | 2070 |
| LIN N. (2001) | 1660 | 1730 |
| WASSERMAN S. FAUST K. (1994) | 1379 | 1656 |
| GRANOVETTER M. THE STRENGTH OF WEAK TIES (1973) | 1297 | 1445 |
| BOURDIEU P. THE FORMS OF CAPITAL (1986) | 1074 | 1127 |
| BURT R.S. STRUCTURAL HOLES AND GOOD IDEAS (2004) | 1045 | 1183 |
In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).
\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]
The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.
This is arguably the more interesting part. Here, we identify the
literature’s current knowledge frontier by carrying out a bibliographic
coupling analysis of the publications in our corpus. This measure uses
bibliographical information of publications to establish a similarity
relationship between them. Again, method details to be found in the tab
Technical description. As you will see, we identify the
main research area, but also a set of adjacent research areas with some
theoretical/methodological/application overlap.
To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.
| label | AU | PY | TI | dgr_int | TC | TC_year |
|---|---|---|---|---|---|---|
| Research Area 1: RA 1: Economic growth (n = 1181, density =0.12) | ||||||
| RA 1: Economic growth | ACEMOGLU D;RESTREPO P | 2018 | THE RACE BETWEEN MAN AND MACHINE: IMPLICATIONS OF TECHNOLOGY FOR GROWTH, FACTOR SHARES, AND EMPLOYMENT | 4.22 | 313 | 78.25 |
| RA 1: Economic growth | BHATTACHARYA M;AWAWORY… | 2017 | THE DYNAMIC IMPACT OF RENEWABLE ENERGY AND INSTITUTIONS ON ECONOMIC OUTPUT AND CO2 EMISSIONS ACROSS REGIONS | 2.18 | 272 | 54.40 |
| RA 1: Economic growth | DIAMOND R | 2016 | THE DETERMINANTS AND WELFARE IMPLICATIONS OF US WORKERS’ DIVERGING LOCATION CHOICES BY SKILL: 1980-2000 | 2.42 | 231 | 38.50 |
| RA 1: Economic growth | JONES CI | 2016 | THE FACTS OF ECONOMIC GROWTH | 5.11 | 100 | 16.67 |
| RA 1: Economic growth | TEIXEIRA AAC;QUEIRÓS ASS | 2016 | ECONOMIC GROWTH, HUMAN CAPITAL AND STRUCTURAL CHANGE: A DYNAMIC PANEL DATA ANALYSIS | 3.16 | 160 | 26.67 |
| RA 1: Economic growth | DIEBOLT C;HIPPE R | 2019 | THE LONG-RUN IMPACT OF HUMAN CAPITAL ON INNOVATION AND ECONOMIC DEVELOPMENT IN THE REGIONS OF EUROPE | 6.28 | 67 | 22.33 |
| RA 1: Economic growth | BEAUDRY P;GREEN DA;SAN… | 2016 | THE GREAT REVERSAL IN THE DEMAND FOR SKILL AND COGNITIVE TASKS | 3.52 | 118 | 19.67 |
| RA 1: Economic growth | BEINE M;BERTOLI S;FERN… | 2016 | A PRACTITIONERS’ GUIDE TO GRAVITY MODELS OF INTERNATIONAL MIGRATION | 2.84 | 135 | 22.50 |
| RA 1: Economic growth | BOVE V;ELIA L | 2017 | MIGRATION, DIVERSITY, AND ECONOMIC GROWTH | 3.80 | 93 | 18.60 |
| RA 1: Economic growth | BERG A;OSTRY JD;TSANGA… | 2018 | REDISTRIBUTION, INEQUALITY, AND GROWTH: NEW EVIDENCE | 4.59 | 73 | 18.25 |
| Research Area 2: RA 2: Human ressource management and firm performance (n = 1034, density =0.36) | ||||||
| RA 2: Human ressource management and firm performance | DECI EL;OLAFSEN AH;RYA… | 2017 | SELF-DETERMINATION THEORY IN WORK ORGANIZATIONS: THE STATE OF A SCIENCE | 5.28 | 609 | 121.80 |
| RA 2: Human ressource management and firm performance | SHIN D;KONRAD AM | 2017 | CAUSALITY BETWEEN HIGH-PERFORMANCE WORK SYSTEMS AND ORGANIZATIONAL PERFORMANCE | 9.63 | 158 | 31.60 |
| RA 2: Human ressource management and firm performance | OSTROFF C;BOWEN DE | 2016 | 2014 DECADE AWARD INVITED ARTICLE REFLECTIONS ON THE 2014 DECADE AWARD: IS THERE STRENGTH IN THE CONSTRUCT OF HR SYSTEM ST… | 6.02 | 211 | 35.17 |
| RA 2: Human ressource management and firm performance | DELERY JE;ROUMPI D | 2017 | STRATEGIC HUMAN RESOURCE MANAGEMENT, HUMAN CAPITAL AND COMPETITIVE ADVANTAGE: IS THE FIELD GOING IN CIRCLES? | 6.84 | 184 | 36.80 |
| RA 2: Human ressource management and firm performance | GUEST DE | 2017 | HUMAN RESOURCE MANAGEMENT AND EMPLOYEE WELL-BEING: TOWARDS A NEW ANALYTIC FRAMEWORK | 2.94 | 382 | 76.40 |
| RA 2: Human ressource management and firm performance | JIANG K;MESSERSMITH J | 2018 | ON THE SHOULDERS OF GIANTS: A META-REVIEW OF STRATEGIC HUMAN RESOURCE MANAGEMENT | 13.30 | 80 | 20.00 |
| RA 2: Human ressource management and firm performance | WALLACE JC;BUTTS MM;JO… | 2016 | A MULTILEVEL MODEL OF EMPLOYEE INNOVATION: UNDERSTANDING THE EFFECTS OF REGULATORY FOCUS, THRIVING, AND EMPLOYEE INVOLVEME… | 5.90 | 179 | 29.83 |
| RA 2: Human ressource management and firm performance | CHOWHAN J | 2016 | UNPACKING THE BLACK BOX: UNDERSTANDING THE RELATIONSHIP BETWEEN STRATEGY, HRM PRACTICES, INNOVATION AND ORGANIZATIONAL PER… | 10.87 | 93 | 15.50 |
| RA 2: Human ressource management and firm performance | BOON C;DEN HARTOG DN;L… | 2019 | A SYSTEMATIC REVIEW OF HUMAN RESOURCE MANAGEMENT SYSTEMS AND THEIR MEASUREMENT | 7.99 | 119 | 39.67 |
| RA 2: Human ressource management and firm performance | SARIDAKIS G;LAI Y;COOP… | 2017 | EXPLORING THE RELATIONSHIP BETWEEN HRM AND FIRM PERFORMANCE: A META-ANALYSIS OF LONGITUDINAL STUDIES | 6.44 | 122 | 24.40 |
| Research Area 3: RA 3: Knowledge and innovation in firms (n = 973, density =0.68) | ||||||
| RA 3: Knowledge and innovation in firms | FORÉS B;CAMISÓN C | 2016 | DOES INCREMENTAL AND RADICAL INNOVATION PERFORMANCE DEPEND ON DIFFERENT TYPES OF KNOWLEDGE ACCUMULATION CAPABILITIES AND O… | 13.08 | 245 | 40.83 |
| RA 3: Knowledge and innovation in firms | WEST J;BOGERS M | 2017 | OPEN INNOVATION: CURRENT STATUS AND RESEARCH OPPORTUNITIES | 15.12 | 181 | 36.20 |
| RA 3: Knowledge and innovation in firms | SCUOTTO V;DEL GIUDICE … | 2017 | KNOWLEDGE-DRIVEN PREFERENCES IN INFORMAL INBOUND OPEN INNOVATION MODES. AN EXPLORATIVE VIEW ON SMALL TO MEDIUM ENTERPRISES | 13.01 | 206 | 41.20 |
| RA 3: Knowledge and innovation in firms | SANTORO G;VRONTIS D;TH… | 2018 | THE INTERNET OF THINGS: BUILDING A KNOWLEDGE MANAGEMENT SYSTEM FOR OPEN INNOVATION AND KNOWLEDGE MANAGEMENT CAPACITY | 8.45 | 275 | 68.75 |
| RA 3: Knowledge and innovation in firms | BOGERS M;FOSS NJ;LYNGS… | 2018 | THE “HUMAN SIDE” OF OPEN INNOVATION: THE ROLE OF EMPLOYEE DIVERSITY IN FIRM-LEVEL OPENNESS | 14.18 | 154 | 38.50 |
| RA 3: Knowledge and innovation in firms | HAANS RFJ;PIETERS C;HE… | 2016 | THINKING ABOUT U: THEORIZING AND TESTING U- AND INVERTED U-SHAPED RELATIONSHIPS IN STRATEGY RESEARCH | 2.78 | 678 | 113.00 |
| RA 3: Knowledge and innovation in firms | FLOR ML;COOPER SY;OLTR… | 2018 | EXTERNAL KNOWLEDGE SEARCH, ABSORPTIVE CAPACITY AND RADICAL INNOVATION IN HIGH-TECHNOLOGY FIRMS | 13.37 | 139 | 34.75 |
| RA 3: Knowledge and innovation in firms | APRILIYANTI ID;ALON I | 2017 | BIBLIOMETRIC ANALYSIS OF ABSORPTIVE CAPACITY | 12.71 | 135 | 27.00 |
| RA 3: Knowledge and innovation in firms | SANTORO G;BRESCIANI S;… | 2020 | COLLABORATIVE MODES WITH CULTURAL AND CREATIVE INDUSTRIES AND INNOVATION PERFORMANCE: THE MODERATING ROLE OF HETEROGENEOUS… | 14.10 | 121 | 60.50 |
| RA 3: Knowledge and innovation in firms | KOBARG S;STUMPF-WOLLER… | 2019 | MORE IS NOT ALWAYS BETTER: EFFECTS OF COLLABORATION BREADTH AND DEPTH ON RADICAL AND INCREMENTAL INNOVATION PERFORMANCE AT… | 18.13 | 91 | 30.33 |
| Research Area 4: RA 4: Social network analysis (n = 636, density =0.41) | ||||||
| RA 4: Social network analysis | BLOCK P;HOFFMAN M;RAAB… | 2020 | SOCIAL NETWORK-BASED DISTANCING STRATEGIES TO FLATTEN THE COVID-19 CURVE IN A POST-LOCKDOWN WORLD | 5.78 | 214 | 107.00 |
| RA 4: Social network analysis | BURT RS;BURZYNSKA K | 2017 | CHINESE ENTREPRENEURS, SOCIAL NETWORKS, AND GUANXI | 6.83 | 107 | 21.40 |
| RA 4: Social network analysis | GONZÁLEZ-BAILÓN S;WANG N | 2016 | NETWORKED DISCONTENT: THE ANATOMY OF PROTEST CAMPAIGNS IN SOCIAL MEDIA | 5.13 | 94 | 15.67 |
| RA 4: Social network analysis | PHUA J;JIN SV;KIM JJ | 2017 | USES AND GRATIFICATIONS OF SOCIAL NETWORKING SITES FOR BRIDGING AND BONDING SOCIAL CAPITAL: A COMPARISON OF FACEBOOK, TWIT… | 1.71 | 257 | 51.40 |
| RA 4: Social network analysis | HIMELBOIM I;SMITH MA;R… | 2017 | CLASSIFYING TWITTER TOPIC-NETWORKS USING SOCIAL NETWORK ANALYSIS | 4.21 | 101 | 20.20 |
| RA 4: Social network analysis | BARNES ML;LYNHAM J;KAL… | 2016 | SOCIAL NETWORKS AND ENVIRONMENTAL OUTCOMES | 3.00 | 119 | 19.83 |
| RA 4: Social network analysis | BARNES M;KALBERG K;PAN… | 2016 | WHEN IS BROKERAGE NEGATIVELY ASSOCIATED WITH ECONOMIC BENEFITS? ETHNIC DIVERSITY, COMPETITION, AND COMMON-POOL RESOURCES | 10.30 | 33 | 5.50 |
| RA 4: Social network analysis | KREAGER DA;SCHAEFER DR… | 2016 | TOWARD A CRIMINOLOGY OF INMATE NETWORKS | 6.27 | 47 | 7.83 |
| RA 4: Social network analysis | KIM JY;HOWARD M;COX PA… | 2016 | UNDERSTANDING NETWORK FORMATION IN STRATEGY RESEARCH: EXPONENTIAL RANDOM GRAPH MODELS | 4.37 | 59 | 9.83 |
| RA 4: Social network analysis | VENKATARAMANI V;ZHOU L… | 2016 | SOCIAL NETWORKS AND EMPLOYEE VOICE: THE INFLUENCE OF TEAM MEMBERS’ AND TEAM LEADERS’ SOCIAL NETWORK POSITIONS ON EMPLOYEE … | 3.75 | 66 | 11.00 |
| Research Area 5: RA 5: Corporate social responsibility (n = 621, density =0.53) | ||||||
| RA 5: Corporate social responsibility | WANG Q;DOU J;JIA S | 2016 | A META-ANALYTIC REVIEW OF CORPORATE SOCIAL RESPONSIBILITY AND CORPORATE FINANCIAL PERFORMANCE: THE MODERATING EFFECT OF CO… | 11.10 | 274 | 45.67 |
| RA 5: Corporate social responsibility | KANG C;GERMANN F;GREWAL R | 2016 | WASHING AWAY YOUR SINS? CORPORATE SOCIAL RESPONSIBILITY, CORPORATE SOCIAL IRRESPONSIBILITY, AND FIRM PERFORMANCE | 7.10 | 218 | 36.33 |
| RA 5: Corporate social responsibility | EL GHOUL S;GUEDHAMI O;… | 2017 | COUNTRY-LEVEL INSTITUTIONS, FIRM VALUE, AND THE ROLE OF CORPORATE SOCIAL RESPONSIBILITY INITIATIVES | 6.97 | 216 | 43.20 |
| RA 5: Corporate social responsibility | BANSAL P;SONG H-C | 2017 | SIMILAR BUT NOT THE SAME: DIFFERENTIATING CORPORATE SUSTAINABILITY FROM CORPORATE RESPONSIBILITY | 5.72 | 240 | 48.00 |
| RA 5: Corporate social responsibility | HAWN O;IOANNOU I | 2016 | MIND THE GAP: THE INTERPLAY BETWEEN EXTERNAL AND INTERNAL ACTIONS IN THE CASE OF CORPORATE SOCIAL RESPONSIBILITY | 8.37 | 160 | 26.67 |
| RA 5: Corporate social responsibility | GREWATSCH S;KLEINDIENST I | 2017 | WHEN DOES IT PAY TO BE GOOD? MODERATORS AND MEDIATORS IN THE CORPORATE SUSTAINABILITY–CORPORATE FINANCIAL PERFORMANCE RELA… | 10.14 | 125 | 25.00 |
| RA 5: Corporate social responsibility | KIM K-H;KIM M;QIAN C | 2018 | EFFECTS OF CORPORATE SOCIAL RESPONSIBILITY ON CORPORATE FINANCIAL PERFORMANCE: A COMPETITIVE-ACTION PERSPECTIVE | 8.04 | 152 | 38.00 |
| RA 5: Corporate social responsibility | MELLAHI K;FRYNAS JG;SU… | 2016 | A REVIEW OF THE NONMARKET STRATEGY LITERATURE: TOWARD A MULTI-THEORETICAL INTEGRATION | 4.18 | 289 | 48.17 |
| RA 5: Corporate social responsibility | RHOU Y;SINGAL M;KOH Y | 2016 | CSR AND FINANCIAL PERFORMANCE: THE ROLE OF CSR AWARENESS IN THE RESTAURANT INDUSTRY | 7.25 | 118 | 19.67 |
| RA 5: Corporate social responsibility | PRICE JM;SUN W | 2017 | DOING GOOD AND DOING BAD: THE IMPACT OF CORPORATE SOCIAL RESPONSIBILITY AND IRRESPONSIBILITY ON FIRM PERFORMANCE | 7.13 | 118 | 23.60 |
| Research Area 6: RA 6: Environmental innovation (n = 620, density =0.54) | ||||||
| RA 6: Environmental innovation | HOJNIK J;RUZZIER M | 2016 | WHAT DRIVES ECO-INNOVATION? A REVIEW OF AN EMERGING LITERATURE | 9.72 | 248 | 41.33 |
| RA 6: Environmental innovation | BOSSLE MB;DUTRA DE BAR… | 2016 | THE DRIVERS FOR ADOPTION OF ECO-INNOVATION | 8.85 | 255 | 42.50 |
| RA 6: Environmental innovation | XIE X;HUO J;ZOU H | 2019 | GREEN PROCESS INNOVATION, GREEN PRODUCT INNOVATION, AND CORPORATE FINANCIAL PERFORMANCE: A CONTENT ANALYSIS METHOD | 6.90 | 225 | 75.00 |
| RA 6: Environmental innovation | DORAN J;RYAN G | 2016 | THE IMPORTANCE OF THE DIVERSE DRIVERS AND TYPES OF ENVIRONMENTAL INNOVATION FOR FIRM PERFORMANCE | 8.46 | 178 | 29.67 |
| RA 6: Environmental innovation | DANGELICO RM | 2016 | GREEN PRODUCT INNOVATION: WHERE WE ARE AND WHERE WE ARE GOING | 6.26 | 237 | 39.50 |
| RA 6: Environmental innovation | HOJNIK J;RUZZIER M | 2016 | THE DRIVING FORCES OF PROCESS ECO-INNOVATION AND ITS IMPACT ON PERFORMANCE: INSIGHTS FROM SLOVENIA | 9.08 | 145 | 24.17 |
| RA 6: Environmental innovation | DEL RÍO P;PEÑASCO C;RO… | 2016 | WHAT DRIVES ECO-INNOVATORS? A CRITICAL REVIEW OF THE EMPIRICAL LITERATURE BASED ON ECONOMETRIC METHODS | 9.72 | 135 | 22.50 |
| RA 6: Environmental innovation | BARBIERI N;GHISETTI C;… | 2016 | A SURVEY OF THE LITERATURE ON ENVIRONMENTAL INNOVATION BASED ON MAIN PATH ANALYSIS | 11.64 | 107 | 17.83 |
| RA 6: Environmental innovation | ZHANG Y-J;PENG Y-L;MA … | 2017 | CAN ENVIRONMENTAL INNOVATION FACILITATE CARBON EMISSIONS REDUCTION? EVIDENCE FROM CHINA | 3.58 | 327 | 65.40 |
| RA 6: Environmental innovation | CAI W;LI G | 2018 | THE DRIVERS OF ECO-INNOVATION AND ITS IMPACT ON PERFORMANCE: EVIDENCE FROM CHINA | 5.26 | 212 | 53.00 |
| Research Area 7: RA 7: Econometric and Statistical Methods and Methodology (n = 557, density =0.3) | ||||||
| RA 7: Econometric and Statistical Methods and Methodology | LI F;MORGAN KL;ZASLAVS… | 2018 | BALANCING COVARIATES VIA PROPENSITY SCORE WEIGHTING | 8.91 | 229 | 57.25 |
| RA 7: Econometric and Statistical Methods and Methodology | AUSTIN PC;LEE DS;FINE JP | 2016 | INTRODUCTION TO THE ANALYSIS OF SURVIVAL DATA IN THE PRESENCE OF COMPETING RISKS | 1.44 | 904 | 150.67 |
| RA 7: Econometric and Statistical Methods and Methodology | ABADIE A;IMBENS GW | 2016 | MATCHING ON THE ESTIMATED PROPENSITY SCORE | 3.00 | 282 | 47.00 |
| RA 7: Econometric and Statistical Methods and Methodology | JOACHIMS T;SWAMINATHAN… | 2017 | UNBIASED LEARNING-TO-RANK WITH BIASED FEEDBACK | 2.43 | 193 | 38.60 |
| RA 7: Econometric and Statistical Methods and Methodology | FONG C;HAZLETTAND C;IM… | 2018 | COVARIATE BALANCING PROPENSITY SCORE FOR A CONTINUOUS TREATMENT: APPLICATION TO THE EFFICACY OF POLITICAL ADVERTISEMENTS | 5.67 | 79 | 19.75 |
| RA 7: Econometric and Statistical Methods and Methodology | ABADIE A;CATTANEO MD | 2018 | ECONOMETRIC METHODS FOR PROGRAM EVALUATION | 4.18 | 105 | 26.25 |
| RA 7: Econometric and Statistical Methods and Methodology | BELL DR;GALLINO S;MORE… | 2018 | OFFLINE SHOWROOMS IN OMNICHANNEL RETAIL: DEMAND AND OPERATIONAL BENEFITS | 1.79 | 214 | 53.50 |
| RA 7: Econometric and Statistical Methods and Methodology | CHAN KCG;YAM SCP;ZHANG Z | 2016 | GLOBALLY EFFICIENT NON-PARAMETRIC INFERENCE OF AVERAGE TREATMENT EFFECTS BY EMPIRICAL BALANCING CALIBRATION WEIGHTING | 5.63 | 61 | 10.17 |
| RA 7: Econometric and Statistical Methods and Methodology | JORDÀ O;TAYLOR AM | 2016 | THE TIME FOR AUSTERITY: ESTIMATING THE AVERAGE TREATMENT EFFECT OF FISCAL POLICY | 2.95 | 107 | 17.83 |
| RA 7: Econometric and Statistical Methods and Methodology | GORDON BR;ZETTELMEYER … | 2019 | A COMPARISON OF APPROACHES TO ADVERTISING MEASUREMENT: EVIDENCE FROM BIG FIELD EXPERIMENTS AT FACEBOOK | 5.86 | 47 | 15.67 |
In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.
\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]
Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).
\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]
More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.
All results are preliminary so far…